It is often necessary to register CT and MR images of the same subject. Unfortunately, the accuracy of available registration methods have not been quantified adequately. We have formulated an objective methodology to quantify the accuracy of any such technique Methods and Results We compared three image registration techniques: (1) stereotactic frame matching (SFM), (2) voxel intensity correlation (VIC) and (3) surface matching (SM). For this, we developed a reference data set using a cadaver head with inserted rigid tubes. CT and MR images were acquired, and the geometric distortion in MR images was corrected using our previously published technique. MR tube centers were detected and mapped into CT-space using the transformations generated by each of the registration methods and compared to CT locations. SFM had improved registration accuracy when corrected for MR distortion; the other methods showed no improvement. After MR distortion correction, SFM consistently had the least error. The error for SM was slightly higher than the other methods. We also investigated the sensitivity of the registration methods to reduced resolution by averaging neighboring voxels. Both VIC and SM resulted in approximately the same amount of residual error, while the error for SFM was considerably less. We also investigated the sensitivity of the registration methods to partial data by considering only subsets of the CT and MR images. When registering the inferior portion of the head, SFM did not show much change; VIC showed a minor increase in error. SM showed a larger reduction of error when registering the superior portion of the head compared to the inferior portion, which may be due to poor surface representation of the inferior portion. Discussion We have developed a methodology to quantify any multimodality image registration technique, and compared the registration accuracy of three widely used techniques.